Systems and Methods for Automated, Rapid Detection of High-Atomic-Number Materials

ABSTRACT

The present invention is directed to an inspection system that has a radiation source, a detector array, an inspection region, and a processing unit, where the processing unit a) obtains a radiographic image, b) segments the radiographic image based on radiation attenuation or transmission, c) identifies at least one segmented area on the radiographic image, d) filters the at least one segmented area using at least one geometric filter, e) generates feature vectors using the filtered segmented area; and f) compares the feature vectors against predefined values to determine whether a high-atomic-number object is present.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application relies on U.S. Provisional No. 61/178,945, filedon May 16, 2010, which is incorporated herein by reference. In addition,the present application is related to U.S. Pat. Nos. 5,638,420;6,567,496; 6,785,357; 7,322,745; 7,368,717; and 7,526,064, which are allherein incorporated by reference in their entirety.

FIELD OF THE INVENTION

The present invention relates generally to methods for detectingspecific classes of materials in radiographic images. Specifically, thematerials of interest are materials that represent security threatsand/or materials that may be hidden or smuggled in baggage and cargobecause of their high intrinsic value, e.g. gold or platinum. Morespecifically, the present invention relates to systems and methods forautomatically and rapidly detecting the presence of high-atomic-number(high-Z) materials such as nuclear materials; nuclear weapons; and,shielding materials that may be used to shield radiation emitted by suchmaterials as well as by radiological dispersal devices, which canprevent them from being detected by radiation detectors. This inventionalso relates to the detection of other types of high-Z materials thatmay be smuggled in cargo due to their value, such as gold and platinumbullion, and works of art and antiquities containing high-Z materials.

BACKGROUND OF THE INVENTION

Radiographic images are produced by the detection of X-rays or gammarays that pass through the object (e.g. the cargo in a truck orcontainer) being inspected. The density, atomic number and the totalamount of material that is present determine how much of the radiationis attenuated and, therefore, the nature and type of radiographic imageproduced. Thus, in addition to determining the average absorption of theX-ray or gamma-ray photons as they travel along the various X-ray paths,it is possible to derive information about the characteristics of thematerial. The identification of areas in the image where high-Zmaterials are present is of specific security interest related to thedetection of certain classes of weapons of mass destruction (WMD).Radiographic images produced by conventional X-ray and gamma-rayscreening systems are typically incapable of determining whether aregion contains high-Z material(s). Instead, an inspector examines theimage to determine if there are any areas considered suspicious due totheir shape, symmetry, size, attenuation or transmittance, etc. Cargocontaining suspicious areas must have the cargo contents removed formanual examination. Inspectors must make their decisions by balancingthe competing objectives of trying to make certain that all actualthreats are detected while maintaining a low false alarm rate to limitthe amount of cargo requiring physical inspection so that the stream ofcommerce is not unduly impacted.

The evaluation of radiographic images by an inspector is subject tohuman factors that can affect threat detection. For example, threatdetection has been found to vary for different inspectors due to suchissues as experience, differences in innate perceptive capabilities,eye/mind fatigue from examining a large number of images, and other suchhindrances.

Also, the time required to analyze a given image depends on the numberof areas or objects initially deemed as being suspicious by thescreening system. A typical image searching/threat detection procedurefor an inspector consists of quickly reviewing the image for highlyattenuating objects by looking for either high levels of attenuation orlow levels of transmission. For example, any given image may contain oneor more highly attenuating objects or areas that need to be examined indetail. For each object or area, the inspector manually creates contrastenhancements using an input device, such as a mouse. Each object thenhas to be evaluated for its total attenuation (or transmission) valuewhereby the inspector selects a region of interest within the object orarea and estimates the average pixel value which reflects the totalattenuation (or transmission) of the X rays or gamma rays along thatpath. Before the net attenuation (or transmission) of the object can beestimated, the attenuation (or transmission) of the surroundingbackground materials has to be analyzed. Then, to generate an estimatednet attenuation (or transmission) of the object, the background must besubtracted from the total attenuation. Finally, the inspector mustexamine the shape and size of the object, and combine these estimateswith the estimated net attenuation (or transmission) to reach aconclusion of whether the object represents a threat. This procedurewould typically have to be repeated for each suspicious object or areawithin an image. If done accurately, this is a very time-intensiveprocedure.

For example, U.S. Pat. No. 7,366,282, assigned to Rapiscan Systems, Inc.and incorporated herein by reference, is “directed towards a method foridentifying an object concealed within a container, comprising the stepsof generating a first set of data using a first stage X-ray inspectionsystem; processing said first set of data using a plurality ofprocessors in data communication with the first stage inspection system;identifying at least one target region from said processed first set ofdata; positioning an inspection region relative to the target regionwherein the inspection region at least partially physically coincideswith the target region; generating the inspection region through asecond stage inspection system; and producing a second set of datahaving a X-ray signature characteristic and fluorescence signaturecharacteristic of the material in the inspection region.” Further, “[i]nanother embodiment, the present invention comprises a single stageinspection system comprising an X-ray diffraction and fluorescencesystem. Contraband, high-Z or other illegal material located within atarget object is identified using a radiation source by passing a targetobject into a C-shaped inspection system; directing an X-ray beam fromsaid radiation source toward a target object; detecting a diffractionsignal using a diffraction detector head; detecting a fluorescencesignal using a fluorescence detector head; and identifying contrabandmaterial using said diffraction signal and said fluorescence signal. Themethod can further comprise the steps of: generating an image of saidtarget object; analyzing the image using an algorithm to evaluateregions of objects based upon a threshold level; segmenting said imageinto regions based upon criteria; further inspecting selected regionssatisfying certain criteria to determine their size and shape; comparingsaid selected regions to threat criteria; and issuing an alarm to aninspector when an object is determined as matching said threat criteriain said comparing step.”

In another example, U.S. Pat. No. 6,347,132, assigned to AnnisTech, Inc.and incorporated herein by reference, discloses “an executable routine50 for automatically detecting nuclear weapons materials. This routineis preferably executed by the signal processor and controller 28 (FIG.1). Step 52 is performed to sample each of the individual detectorelements of the transmission detector 22 (FIG. 1) as the object underinspection 12 (FIG. 1) is scanned relative to the fan beam 20 (FIG. 1),and digitize and store the sampled values. Test 54 performs a thresholddetection on the sampled values to identify any areas of unusually highabsorption within the image of the object under inspection. That is,since the nuclear weapons materials absorb x-rays significantly morethan any other materials, the magnitude of the sampled signalsassociated with areas within the object under inspection having nuclearweapons materials will be significantly different than the surroundingareas. Therefore, threshold detection is a suitable automatic detectiontechnique. Alternatively, spatial frequency analysis may also be used todetect large changes in the sampled signal magnitude, which may then beanalyzed to determine whether or not the large changes in magnitude areconsistent with nuclear weapons materials. In any event, detection ofthe nuclear weapons materials is automatic. Similarly, the region ofhigh attenuation identified in the transmission image is examined in thescatter image (if the pencil beam system is employed). A negative resultin the scatter image reinforces the result from the transmission beamanalysis. If nuclear weapons' materials are detected, step 56 provides awarning annunciator that may be displayed on the display, initiates anaudio alarm, or provides other suitable warning devices.”

In yet another example, U.S. Pat. No. 7,492,682, assigned to GE HomelandProtection, Inc. describes “[a] method for inspecting a container forcontraband, said method comprising: positioning the container on aplatform configured to support the container, the platform rotatablycoupled to a frame that is movably coupled to a base defining an axis,the frame movable with respect to the base in a direction parallel tothe axis, and the platform movable with the frame and rotatable withrespect to the frame about the axis; producing X-ray beams having atleast one energy distribution and transmitting the X-ray beams throughthe container as the container rotates about the axis and moves in adirection parallel to the axis; detecting the X-ray beams transmittedthrough the container with an array of detectors to generate signalsrepresentative of the detected radiation; and processing the signals toproduce images of the container and contents of the container togenerate a map for the container including at least one of a CT number,a density and an atomic number corresponding to the contents within thecontainer.”

Conventional prior art threat detection uses various techniques such asconventional radiography, dual-energy imaging, resonantabsorption/fluorescence, computed tomography (CT) systems, dual-stageX-ray diffraction and fluorescence systems, to produce radiographicimages that are either inspected manually for threat detection and/oranalyzed using software routines.

For example, high-energy dual-energy techniques have been employed inconventional systems. Multi-energy inspection employs scanning largeobjects with two or more energies in the megavoltage region, i.e. 6 MVand 9 MV. This technique is based on the difference of the X-rayattenuation for materials with different atomic numbers. Collectingtransmission information for multiple energies enables determining theatomic number of a material along the X-ray path length.

U.S. Pat. No. 7,483,511, assigned to GE Homeland Protection, Inc.describes “[a] method of determining a presence of items of interestwithin a cargo container, the method comprising: obtaining informationfrom an initial radiation scan of at least one of the cargo containerand contents therein, the obtaining comprising: transmitting a screeningradiation beam along a screening portion of the cargo container at ascreening scan rate; detecting radiation received in response to thetransmitting the screening radiation beam; and analyzing the detectedradiation received in response to the transmitting the screeningradiation beam to develop information regarding the initial radiationscan; identifying a target portion of the cargo container in response tothe information obtained, wherein the screening portion is larger thanthe target portion; transmitting a target radiation beam along thetarget portion of the cargo container at a target scan rate, the targetscan rate being different than the screening scan rate; detectingradiation received in response to the transmitting; analyzing thedetected radiation for a presence of items of interest; and in responseto the analyzing, generating a first signal indicative of the presenceof the items of interest, or generating a second signal indicative of anabsence of the items of interest.”

Further, U.S. Pat. No. 7,286,638, assigned to Passport Systems, Inc.describes “[a] method for analyzing material in a voxel of a target, themethod comprising: illuminating the voxel with a photon beam; measuringa first number of photons scattered from the voxel in a first energyrange and in a first measurement direction; measuring a second number ofphotons scattered from the voxel in a second energy range and in asecond measurement direction; determining a ratio of the first number ofphotons to the second number of photons; determining an average atomicnumber of the material in the voxel using the ratio; and generating asignal based upon the average atomic number determined.”

And still further, United States Patent Publication Number 20090323889describes a “[s]ystem and method for XRD-based false alarm resolution incomputed tomography (“CT”) threat detection systems. Following a scan ofan object with a megavoltage CT-based threat detection system, asuspicious area in the object is identified. The three dimensionalposition of the suspicious area is used to determine a ray path for theXRD-based threat detection system that provides minimal X-rayattenuation. The object is then positioned for XRD scanning of thesuspicious area along this determined ray path. The XRD-based threatdetection system is configured to detect high density metals (“HDMs) aswell as shielded Special Nuclear Materials (“SNMs”) based on cubic ornon-cubic diffraction profiles.”

The prior art, however, suffers from severe limitations for thehigh-throughput inspection of large dense cargo. For example, inspectionmethods based on dual-energy and fluorescent methods have difficultieswith threat detection within dense, highly attenuating cargo; CT systemsare not practical for inspection large cargo because of size and speedconstraints. Further, software routines based on threshold detectionhave not proven effective due to the inability to distinguish betweenthe presence of high-Z materials and areas that have high attenuationdue to their thickness and density.

What is therefore needed is a method for automatically and rapidlyanalyzing radiographic images, specifically for high-atomic-number(high-Z) materials, where “high-Z” refers to materials in the periodictable of atomic number 72 (Hafnium) and above.

What is also needed is a method for accurately detecting high-Zmaterials in very large and dense objects (e.g. containers containingmetals and other dense cargo) with an inspection and analysis speed thatresults in minimal additional delay in the clearing of cargo.

What is also needed is a method that implements complementary modulesthat analyze the radiographic image using both threshold and gradientdetection techniques along with characteristic geometric and physicalconsiderations to reduce false alarms while automatically and rapidlyrendering “High-Z”/“Clear” decisions.

SUMMARY OF THE INVENTION

In one embodiment, the present invention is directed toward aninspection system comprising: a radiation source; a detector array; aninspection region bounded by said radiation source and detector array; aprocessing unit, wherein, through operation of at least one processor,at least one memory, and programmatic instructions, said processing unitobtains data representative of a radiographic image; segments said databased on radiation attenuation or transmission; identifies at least onesegmented area within said data representative of said radiographicimage; filters said at least one segmented area using at least onegeometric filter; generates a plurality of feature vectors using saidfiltered segmented area; and compares said feature vectors againstpredefined values to determine whether a high-atomic-number object ispresent.

Optionally, the radiographic image has a spatial resolution of at least0.25% of a minimum size of a threat object. The radiation source is atleast one of X-ray or gamma-ray radiation. The processing unit generatesa map of said segmented data representative of said radiographic imageby determining local maximum peak attenuation values. The processingunit generates a map of said segmented data representative of saidradiographic image by determining minimum transmission values andapplying edge gradient calculations. The geometric filter is at leastone of shape, symmetry, size or homogeneity. The size filter is appliedto at least one segmented area to identify dimensions selected on thebasis of spatial resolution or penetration. The shape filter is appliedto at least one segmented area to identify a spatial aspect ratio ofless than 20. The segmented area has a first number of pixels andwherein a second defined area has a second number of pixels and whereinthe homogeneity filter is applied to determine a ratio of said firstnumber of pixels to said second number of pixels.

Optionally, the processing unit generates a plurality of feature vectorsusing said filtered segmented area by: obtaining an image of saidfiltered segmented area; estimating background attenuation around saidfiltered segmented area; subtracting the background attenuation fromsaid filtered segmented area to generate a net attenuation of thefiltered segmented area; estimating dimensions of the area of interestusing said net attenuation of the filtered segmented area; calculatingan attenuation of the filtered segmented area as if it were a high-Zmaterial; and comparing the calculated attenuation of the filteredsegmented area of interest to the net attenuation of the filteredsegmented area.

Optionally, the feature vectors comprise at least one of maximumattenuation, net attenuation, a ratio of attenuation to an area of asuspicious object, a gradient of a suspicious object along a boundary,and a difference produced between measured background correctedattenuation and calculated attenuation. The feature vectors are comparedagainst predefined values to determine whether a high-atomic-numberobject is present.

In another embodiment, the present invention comprises an inspectionsystem comprising a processing unit, wherein said processing unit:segments data of a first radiographic image, which is representative ofa first view of an object, and a second radiographic image, which isrepresentative of a second view of the object, based on radiationattenuation or transmission; filters at least one segmented area usingat least one filter for each of said images; generates a plurality offeature vectors using said filtered segmented area for each of saidimages; and determines whether a high-atomic-number object is presentusing said feature vectors for each of said images.

Optionally, each of said radiographic images is produced using at leastone of an X-ray or gamma-ray radiation source. The processing unitactivates an alarm if each of said images indicates the presence of ahigh atomic number object. The filter is at least one of shape,symmetry, size or homogeneity. The size filter filters said at least onesegmented area to identify dimensions selected on the basis of theinspection system's spatial resolution or penetration. The shape filterfilters said at least one segmented area to identify a spatial aspectratio of less than 20.

In another embodiment, the present invention is an inspection systemcomprising a processing unit, wherein said processing unit: segmentsdata of a first radiographic image, which is representative of an objectand generated at a first energy level, and a second radiographic image,which is representative of the object and generated at a second energylevel; filters at least one segmented area using at least one filter foreach of said images; generates a plurality of feature vectors using saidfiltered segmented area for each of said images; performs a ratiooperation on said plurality of feature vectors, resulting in a ratiofeature vector; and determines whether a high-atomic-number object ispresent using said ratio feature vector. The processing unit activatesan alarm if each of said images indicates the presence of a high atomicnumber object.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features and advantages of the present invention will beappreciated, as they become better understood by reference to thefollowing detailed description when considered in connection with theaccompanying drawings wherein:

FIG. 1 is a block diagram illustrating steps of one embodiment of aradiography-based method of the present invention for automatically andrapidly detecting the presence of high atomic-number (high-Z) materialsfrom a conventional radiographic image;

FIG. 2 is an illustration of a conventional X-ray radiographic imageshowing the attenuation produced by the contents of a cargo container;

FIG. 3A is an initial segmented map of suspicious objects or areas forfurther analysis of the X-ray radiographic image of FIG. 2, using thepresent invention;

FIG. 3B is an illustration of at least one model used to estimate thebackground around the object of interest, using the present invention;

FIG. 3C is an illustration of five objects of interest for furtherfeature vector analysis, using the present invention;

FIG. 3D is a feature vector table used in the present invention thatcontains representative values;

FIG. 4 is a depiction of suspicious objects or areas derived from themethod of the present invention for automatically and rapidly detectingthe presence of high-Z materials;

FIG. 5 is an illustration of an X-ray radiographic image of a cargocontainer after analysis using the methods of the present invention forautomatically and rapidly detecting the presence of high-Z materials;

FIG. 6 is a representative diagram of one embodiment of the method ofthe present invention integrated with a conventional X-ray transmissioncargo container screening system; and

FIG. 7 is a block diagram illustrating steps of one embodiment of adual-energy radiographic imaging method of the present invention forautomatically and rapidly detecting the presence of high-Z materials.

DETAILED DESCRIPTION OF THE DRAWINGS

The present invention is directed towards methods for detecting specificclasses of materials (i.e. high-Z) within radiographic images. Moreparticularly, the present invention is directed towards a threatdetection method for automatically and rapidly analyzing radiographic(X-ray, gamma-ray, etc.) images of cargo, such as crates, trucks, seacontainers, baggage, and other cargo, for security threats and othertypes of contraband, in particular, high-atomic-number (high-Z)materials. Thus, in one embodiment, the present invention is directedtowards increasing screening throughput and eliminating the need for aninspector or security screening system operator to manually examinesuspicious areas within the radiographic image.

For purposes of this invention, “high-Z” refers to materials in theperiodic table of atomic number 72 (Hafnium) and above, with theexception of Polonium (84) which, due to its very low density, fallsoutside of the effective range of the methods of the present invention.

In one embodiment, the present invention is directed towards acontraband detection method that efficiently detects high-Z materials,such as, but not limited to, special nuclear material(s) (SNM) (i.e.uranium, plutonium) in an assembled nuclear device; a separate quantityof SNM intended for the eventual assembly into a nuclear device; and,one of a number of high-Z materials (e.g. tungsten, lead) typically usedto shield radioactive materials to prevent the emitted radiation frombeing detected by the arrays of passive detectors that are being placedinto operation at a number of global ports of entry. Examples ofradiation-emitting threats include SNM and radioactive isotopes thatcould be used in a radiological dispersal device (i.e., “dirty bomb”).The present invention also provides a method for detecting other typesof contraband including high-Z materials of high value, such as gold andplatinum, and art objects containing high-Z materials.

The threat detection methods of the present invention advantageously usephysical properties such as material density, mass absorptioncoefficient, and dimension. In one embodiment, the threat detectionmethod of the present invention requires a much shorter analysis timeand, thus, allows for higher system throughput. The time to analyze agiven radiographic image depends on the number of objects selected asbeing suspicious during the analysis.

In a conventional system, a typical procedure consists of an inspectormanually reviewing the image for objects that are highly attenuating.For example, if multiple objects that are highly attenuating areidentified, the inspector would need to make contrast enhancements witheach object using a computer and input device, such as mouse. Eachobject has to then be evaluated for its total attenuation (ortransmission) value by using the computer to select a region of interestwithin the object and making an estimate of the average attenuation (ortransmission) value, which reflects the total attenuation (ortransmission) along the X-ray path through the cargo. Before the netattenuation (or transmission) of the object can be estimated, theattenuation (or transmission) of the surrounding background materialshas to be analyzed. Then, to generate an average net attenuation (ortransmission) of the object, the background must be subtracted from thetotal attenuation (or added to the transmission). Finally, the inspectormust examine the shape and size of the object, and combine theseestimates with the estimated net attenuation (or transmission) to reacha conclusion of whether the object represents a threat. This procedurewould have to be repeated for each object and, therefore, if performedaccurately, would be a very time-intensive procedure.

In using the threat detection methods of the present invention, however,the decision time ranges from typically less than one second for cargodetermined not to have any suspicious objects, to less thanapproximately 5 seconds for cargo such as the image shown in FIG. 2having a plurality of objects or areas of interest, depending upon theprocessing speed of the computer that is used. In other embodiments ofthe present invention, as described below, decision processing time mayincrease or decrease, depending upon the complexity of the cargo and/orscan.

In prior art methods, threat detection has been found to vary fordifferent inspectors due to such issues such as experience, differencesin innate perceptive capabilities, eye/mind fatigue from examining alarge number of images, among other factors. Thus, in addition to imageanalysis speed, the threat detection methods of the present inventionare advantageous in that they are capable of performing a consistentanalysis using the same physical principles and decision criteria forall images. Thus, threat detection is made less susceptible to humanfactors that can affect the analysis of radiographic images by aninspector. Further, automated detection using the present invention isadvantageous for detecting threats within partially saturated areas(i.e. areas not fully penetrated by the X-ray beam). Because of thestatistical uncertainty in the attenuation or transmission values ofpartially saturated regions, much more elaborate manual procedures wouldbe required in order for an inspector to analyze these regions andsubsequently make a decision.

The present invention is directed towards multiple embodiments. Thefollowing disclosure is provided in order to enable a person havingordinary skill in the art to practice the invention. Language used inthis specification should not be interpreted as a general disavowal ofany one specific embodiment or used to limit the claims beyond themeaning of the terms used therein. The general principles defined hereinmay be applied to other embodiments and applications without departingfrom the spirit and scope of the invention. Also, the terminology andphraseology used is for the purpose of describing exemplary embodimentsand should not be considered limiting. Thus, the present invention is tobe accorded the widest scope encompassing numerous alternatives,modifications and equivalents consistent with the principles andfeatures disclosed. For purpose of clarity, details relating totechnical material that are known in the technical fields related to theinvention have not been described in detail so as not to unnecessarilyobscure the present invention.

In addition, one of ordinary skill in the art would appreciate that thefeatures described in the present application can operate on anycomputing platform including, but not limited to: a laptop or tabletcomputer; personal computer; personal data assistant; cell phone;server; embedded processor; main-frame, DSP chip or specialized imagingdevice. Additionally, the programmatic code can be compiled (eitherpre-compiled or compiled “just-in-time”) into a single applicationexecuting on a single computer, or distributed among several differentcomputers operating locally or remotely to each other. It should furtherbe appreciated that all of the method steps disclosed herein, includingany and all processing or analytical functions, are implemented in suchprogrammatic code stored in a memory and executed on by at least oneprocessor in the computing platform.

In one embodiment, the threat detection methods of the present inventionoperate by first receiving, on a computing platform, a radiographicimage of an object from an X-ray imaging system which typicallycomprises a radiation source positioned opposite to, or away from, adetector array. At least part of the area bounded by the radiationsource and detector array is an inspection region, through which thecargo being inspected passes, or is positioned. Exemplary X-ray imagingsystems are shown in U.S. Pat. Nos. 5,638,420; 6,567,496; 6,785,357;7,322,745; 7,368,717; and 7,526,064, which are all herein incorporatedby reference in their entirety. It should be noted that the softwareapplication of the present invention can be used with any X-ray orgamma-ray imaging system that includes a computing platform. In oneembodiment, the screening system acquires the original image, which isthen processed by the methods of the present invention.

The X-ray imaging system is in electrical communication, either wired orwirelessly, with the computing platform. The threat detection methodsthen perform a first level analysis to generate a first “suspiciousobject” binary map by measuring a number of physical attributes. Eacharea on the initial binary map is used as a mask to electronically cropout part of the X-ray radiographic image for analysis, including itssurrounding background attenuation (or transmission) and physicalcharacteristics such as attenuation, size, and shape. Then, a decisionis made of whether that area or portion could represent a high-Z object.This decision process results in a second binary map, which highlightsthose regions that represent potential high-Z threats.

While described with respect to its use in an X-ray imaging system, itshould be noted that the threat detection methods of the presentinvention can be used with X-ray and gamma-ray sources of variousenergies and intensities, whereby a sufficient amount of radiation (Xrays or gamma rays) penetrates the object under inspection so as toproduce measurable signals in the detector above noise levels.Therefore, the required source energy and intensity is dependent on thephysical dimension of the cargo along the direction of the X rays andthe composition of the cargo, such as its density and atomic number.Further, the methods of the present invention can be used with X-ray orgamma-ray beams that are constant in intensity or where the intensity orenergy is modulated. Still further, the present invention can be usedwith systems that employ radiation beams that vary in energy or withsystems that produce radiation of different energy or with systems thatuse a low-energy detector in-line with a high-energy detector,including, but not limited to dual-energy and multi-energy radiographicimaging systems.

FIG. 1 is a block diagram illustrating steps of a radiographic imagingmethod of the present invention for automatically and rapidly detectingthe presence of high-Z materials. In one embodiment, the threatdetection methods of the present invention, in step 105, receives aradiographic image from an imaging system 106, such as an X-ray imagingsystem. An exemplary radiographic image 200, of a cargo container, isshown in FIG. 2, showing objects within the cargo container.

The capability of the methods of the present invention to detectspecific high-Z materials and the alarm rate associated therewith isdependent upon image quality. Thus, the imaging system of the presentinvention should have sufficient spatial resolution so that it is ableto resolve high-Z objects. In one embodiment, a spatial resolution thatis approximately 25% of the minimum size of the high-Z object to bedetected is adequate. For example, if the minimum size of the high-Zobject is 1 inch, then the spatial resolution of the imaging systemshould be at least 0.25 inches. For systems with poorer resolution, theprobability of detection and the false alarm rate can be adverselyaffected. The detection of a high-Z object is not strongly dependent onthe contrast resolution of the image unless areas of the image arepartially saturated; in such cases, high contrast resolution isadvantageous.

Other factors can also affect the image quality and, hence, thesuccessful detection of threats. Under some conditions, image artifactscan result from the specific design of the imaging system. For example,the presence of structural components of the cargo container, such asthe metal ribs present in sea cargo containers, can affect the accuracyof the methods of the present invention. These ribs may be present inthe radiographic image as narrow vertical lines that may complicate theability to segment high-Z objects if they appear in the image at thelocation of a suspicious area with high attenuation or low transmission.Since the methods disclosed herein can be used with virtually any typeof X-ray imaging system, the extent of any image artifacts will besystem and cargo container dependent. Thus, image and signal processingtechniques, determined on a case-by-case basis, would be needed tominimize artifacts.

Referring back to FIG. 1, the radiographic image 106 serves as the inputto the threat detection methods of the present invention. The image 106is subsequently segmented in step 110, based on the X-ray attenuation(or transmission) of the object. X-ray attenuation of an object ismaterial-dependent, and is governed by the following equation for X-rayor gamma-ray radiation at a nominal energy, E:

$\begin{matrix}{\frac{I(E)}{I_{o}(E)} = ^{{- {\mu {(E)}}}t}} & {{EQUATION}\mspace{14mu} 1}\end{matrix}$

where μ is the linear attenuation coefficient and t is the X-ray beampath length through the object

Accordingly, by knowing, detecting, measuring, or determining the X-rayinput, output, and beam path length, one can determine the linearattenuation coefficient, which is indicative of the material beingscanned. In one embodiment, during the image segmentation process ofstep 110, the edge gradients of the objects in the image are employed toidentify potential high-Z areas in the presence of a highly clutteredbackground, produced by complex cargo with high-spatial frequencies.This is effective since a high-Z object will produce a high attenuationvalue or low transmission value in the radiographic image and will alsohave a large attenuation or transmission gradient along its edges.

The image segmentation is performed by using a processor that loads froma memory device (hard disk, RAM, ROM, RAID array, flash drive, USBdevice, or other memory) the data representative of the radiographicimage and that subjects the data to a program which performs the imagesegmentation calculations as described herein.

The image segmentation performed in step 110 results in an initial mapof potential high-Z objects or areas by determining local maximumattenuation (or minimum transmission) values with multi-thresholdsegmentation. Alternatively, the initial map of potential high-Z objectsor areas can be generated by determining local minimum transmissionvalues with multi-threshold segmentation. FIG. 3A is an initialsegmented map 300 of the radiographic image shown in FIG. 2 showingpotential high-Z objects or areas based on local maximum attenuation 305that would need further analysis.

Referring back to FIG. 1, next, in a geometric-based module 111, aplurality of filters are applied to the segmented radiographic image toreduce the number of segmented areas for further analysis by applyinggeometric constraints. In one embodiment, the geometric constraintsapplied are predetermined metes and bounds in terms of shape, symmetry,size and homogeneity. The filters are applied by using a processor thatloads from a memory device (hard disk, RAM, ROM, RAID array, flashdrive, USB device, or other memory) the data representative of thesegmented images of the radiographic image and that subjects the data toa program which performs size, shape, and homogeneity calculations, asdescribed herein.

In one embodiment, in step 115, a size filter excludes regions that areeither smaller than the minimum size of objects to be detected or largerthan the size of an object through which the penetration of theradiation beam becomes insufficient. The method of the present inventioncan be employed with radiographic systems of various energies andperformance capabilities ranging from high-resolution, low-penetrationbaggage inspection systems to lower resolution, but higher penetrationsystems designed for the inspection of dense cargo carried in trucks,sea containers, and other dense cargo. In selecting the dimensions to beused in the methods of the present invention, consideration should begiven to the performance of the radiographic system that is acquiringthe image data, in particular, the system's spatial resolution andpenetration. Generally, the smallest size of the object to be detectedshould be set to a value that is approximately four times greater thanthe system's spatial resolution; the larger size dimension should be onefor which reasonable detector signal-to-noise levels are achieved (onthe order of a signal to noise ratio of 3 to 1) and limited imagesaturation occurs. For example, the Rapiscan Systems' Eagle™ Portal, a 6MV cargo imaging system, achieves a spatial resolution of 0.25 inchesand a penetration limit of 425 mm of steel. Thus, the minimum size ofthe high-Z object would be 1 inch (4 times greater than the spatialresolution) and the maximum size would be approximately 400 mm of steel.Although the dimensions can be set to different values, the competinginterests of both the penetration and resolution of the system must beconsidered since, in combination, they largely determine the probabilityof detection and the false alarm rates that are experienced duringoperation. In the case of insufficient penetration, the segmented objector area is labeled with a bounding box for the inspector.

In step 116, a shape filter eliminates objects with an aspect ratiogreater than a pre-determined, pre-set value and retains objects withcommon primitive shapes, such as cubes, cylinders and spheres. In oneembodiment, the pre-determined aspect ratio is set between 4 and 20. Theaspect ratio of the object is derived by calculating the ratio of thelengths of the major axis to the minor axis of the object. Thus, in oneembodiment, in applying the shape filter of the present invention, anyobject having an aspect ratio of greater than 20 is discarded. For morecomplex shapes, namely, a combination of primitive shapes, a symmetryfeature is used for shape determination. The symmetry analysis isapplied to at least one segmented area to characterize thetwo-dimensional boundary of the area as a one-dimensional function ofthe polar angle from the centroid of the segmented area. Thisone-dimensional function is analyzed to quantify the shape of thesegmented area and its degree of symmetry through the magnitude andperiodicity of the function. As an example, the symmetry filter may begenerated through radial Fourier expansion and other techniques that areknown to those skilled in the art of automated characterization ofshapes through machine vision.

In step 117, a homogeneity filter rejects any regions that containpatterns of scattered clusters of pixels connected by only a few pixels.In one embodiment, the homogeneity filter is defined by the ratio of thenumber of the pixels in the segmented area to the number of pixelscontained in a bounding box around the segmented area. In oneembodiment, the predetermined homogeneity filter is set between 40% and80%, depending on the desired sensitivity. In one embodiment, thepredetermined minimum ratio of the homogeneity filter is set at 50%.Thus, in applying this predetermined homogeneity filter, any regionswhere the ratio of the number of the pixels in the segmented area to thenumber of pixels contained in a bounding box around the segmented areais less than 50% are discarded. While different ratio values can beemployed, the use of small ratios can contribute to a larger number offalse positives.

Optionally, additional filters may also be applied to potential high-Zobject areas in the radiographic image. These include the use of textureto identify areas for further analysis as a potential high-Z object andsymmetry filters that could be used to identify shell-like high-Zobjects and establish a shape or boundary vector. The boundary vectorcan then be compared to predetermined boundary vectors on the basis ofshape, which is invariant to translation, rotation and scaling, andpredetermined geometrical landmarks that describe a particular high-Zobject of interest. Other geometrical filters may include form factor,which is a measure of the elongation of the object, roundness, andcompactness. Some filters designed for removal of certain imageartifacts, such as directional streak filters and noise smoothingfilters, could also be applied in conjunction with geometric filters,when there are artifacts present. Additionally, the filters can be usedin parallel or serially.

In step 125, the resultant geometric-filtered image, comprising at leastone potential high-Z area, is communicated to a characterization module129 to analyze each region within the image map and generate a featurematrix, which includes the outputs of all the functions within thecharacterization module, for ultimate decision analysis. Within thecharacterization module 129, the region of interest (ROI) around eachsuspicious area is obtained in step 130, by cropping the radiographicimage using the object map as a mask. The characterization module 129 isapplied by using a processor that loads from a memory device (hard disk,RAM, ROM, RAID array, flash drive, USB device, or other memory) the datarepresentative of the filtered images of the radiographic image and thatsubjects the data to a program which performs the vector analysesdescribed herein.

In step 135, at least one model is used to estimate the backgroundaround the object of interest. FIG. 3B is an illustration of thebackground estimation model used to estimate the background around theobject of interest in one embodiment of the present invention. As shownin FIG. 3B, in step 135 a, image 350 is created as object 352 issuperimposed on top of a non-uniform background 353, which is selectedby enlarging the region of interest symmetrically by an amount dependenton the original size of the region of interest and the spatial frequencyof the surrounding cargo. In step 135 b, the background function thenestimates the attenuation (or transmission) of the background objects byusing the surrounding attenuation information to linearly fit theattenuation pixel by pixel within the region of interest, as shown inimage 355. In step 135 c, the background attenuation derived in step 135b (or image 355) is subtracted from the original image 350. Theresultant image 360 is the net attenuation due to the object.

The dimensions (such as width, for example) of the object are estimatedat step 145. In one embodiment, this estimation is performedsubstantially simultaneously with step 135. After the object is croppedout in step 135 c, shown in FIG. 3B, the vertical and horizontaldimensions of the object are derived by using line profiles along thehorizontal and vertical directions over the object.

The attenuation of the object is calculated, as if the object wascomprised of a high-Z material, in step 150, using an assumption thatthe thickness of the object is similar to other dimensions, namely theobject's horizontal and vertical dimensions that are measurable in theimage. The resultant calculated attenuation derived from step 150 isthen compared, in step 155, to the net attenuation described withrespect to FIG. 3B and shown as image 360. The comparison results in anelement in the feature vector used for further decision analysis.

The outcome of the filtering is thus a set of elements that comprise afeature vector for each of the suspicious objects or areas segmented inthe radiographic image. The elements in the base feature vector comprisemaximum attenuation, net attenuation, the ratio of the attenuation tothe area of the suspicious object and the gradient of the suspiciousobject along the boundary, and the difference produced between the netattenuation and the calculated attenuation. The resulting featurevectors for each potential high-Z area are then evaluated againstestablished decision-making rules, in step 160, to determine whether ahigh-Z object is present and to render a “Clear” or “High-Z” decision.

It should be appreciated that, if at any programmatic step, no imageareas are found to satisfy the image segmentation, geometric-basedfilters, or characterization analyses, the inspection process can bestopped and the cargo can be deemed inspected and cleared.

FIG. 3C is a representative example of a subset of the resulting featurevectors and a set of decision-making rules. In one embodiment, thefeature vectors shown in FIG. 3C derived by the characterization moduleas discussed above, are only for those regions segmented from thegeometric-based module. As shown in FIG. 3C, five listed objects 371,372, 373, 374, and 375 are sent to the decision analysis module, withtheir feature vectors. FIG. 3D is a representative feature vector table,where V1 is maximum attenuation, V2 is net attenuation, V3 is the ratioof the maximum net attenuation to area, and V4 is the vertical gradient,with values for each of objects 371, 372, 373, 374, and 375, shown inFIG. 3C. In one embodiment, the following is representative of a typicalrule for an inspection system based on attenuation, where the maximumattenuation is equivalent to 25,000. The decision analysis is used todetermine whether the system should alarm indicating a threat condition:

If V1 ≦ 24,500, then If V2 > 5000 AND V3 > 50 AND V4 > 600, THEN ALARMElse CLEAR End Else SEND to Saturation Procedure EndWhen the “if conditions” are met, i.e., V1 is less than it preset valueand all of the remaining feature vector elements exceed preset values,the methods of the present invention are programmed to identify thatobject as high-Z and subsequently draw a red box labeled “High-Z” aroundthe object in the radiographic image.

As a result, in the example provided, objects 373, 374, and 375 willalarm as potential threat items. The precise numerical values containedin this rule can be adjusted to achieve a given probability of detectionand false alarm rate. Additionally, similar rules can be developed forsystems that rely on transmission and for systems with different scalesfor the maximum attenuation or transmission.

FIG. 4 is a final map of suspicious objects or areas, binary image 400,derived from the methods of the present invention for automatically andrapidly detecting the presence of high-atomic-number (high-Z) materialsdescribed above. Binary image 400 results from the decision analysis andincludes three highlighted regions 405 that represent potential high-Zalarms.

These three highlighted regions are then used to identify the high-Zalarm regions in the radiographic image using boxes 505 shown in FIG. 5.Thus, FIG. 5 is a radiographic image of a cargo container after analysisusing the methods of the present invention for automatically and rapidlydetecting the presence of high-atomic-number (high-Z) materials.

In one embodiment, the high-Z detection methods of the present inventionare capable of using signal analysis techniques to analyze partiallysaturated regions and, subsequently, group pixels based on their spatialcorrelations and noise frequency patterns.

Partial penetration or partial saturation occurs when an object itselfhas sufficiently high attenuation or is superimposed on heavilyattenuating materials, such as thick steel plates, as shown in FIGS. 6AAND 6B. FIG. 6A is a radiographic image, showing high-Z objects hiddenbehind 15 inches of steel. As can be seen in FIG. 6A, in radiographicimage 600, some pixels are saturated and observable as black-coloredregions 605. Once saturation is reached, estimating the net attenuationbecomes challenging as these saturated regions have the same maximumpixel values. The distribution of black pixels is different between thecircular objects (low frequency) and the area above them (highfrequency), which is due to the attenuation of the 15-inch steel plates.Persons of ordinary skill in the art would appreciate that while it ispossible for human vision to discern this pattern difference, it ischallenging for automatic methods on computers to identify these areasas separate objects.

Thus, in order to estimate the attenuation values in partially saturatedcases, a noise reduction step 127 is performed. The noise reduction stepis similar to the segmentation step 110 of FIG. 1, described previouslyto generate a map of suspicious areas for further processing. Once theobjects are segmented out, in an analogous fashion to the segmentationstep described with respect to FIG. 1, a noise-reduction technique, suchas the use of wavelets, well known to persons of ordinary skill in theart is applied to both the object and the background. The noisereduction technique is applied by using a processor that loads from amemory device (hard disk, RAM, ROM, RAID array, flash drive, USB device,or other memory) the data representative of the segmented images of theradiographic image and that subjects the data to a program whichperforms noise-reduction calculations as known to persons of ordinaryskill in the art.

For these partially saturated cases, it is possible to estimate theattenuation values after the noise reduction step 127. It should benoted that noise reduction is a necessary step for partially saturatedcases, and is performed after segmentation and prior to thephysics-based characterization step. The estimated attenuation values,along with other features, such as background attenuation, thepercentage of the saturated pixels within an object, and object sizes,are fed into the detection decision rules for classification. In anoptional embodiment, once the segmentation and noise reduction steps areperformed, objects or areas containing a high-Z material (i.e.,tungsten) hidden behind shielding materials are highlighted. In oneembodiment, the objects or areas containing high-X materials arehighlighted by drawing a box around the suspicious area.

Insufficient penetration occurs when the attenuation of the X-ray beamby the material in the cargo is greater than the dynamic range of theX-ray imaging system. In these areas, the image is completely saturatedand dominated by image noise. Therefore, the object cannot bedifferentiated from the background. In such cases, the threat detectionmethods of the present invention segments these areas and labels them,such as by highlighting the areas or drawing a box around them, toindicate that they are saturated in the radiographic image.

In one embodiment, the threat detection methods of the present inventionare implemented as software installed and executed on a computerassociated with a radiographic threat detection system. In oneembodiment, the radiographic threat detection system is a cargo scanningsystem. FIG. 6 is a diagrammatic illustration showing the use of a cargoX-ray scanning system 600, comprising X-ray source 605 and transmissiondetectors 610. The attenuated X-ray beam 607 is captured by detectors610 after transmission through the cargo container 615. The detectorsignals are then digitized and presented as a radiographic image (notshown) on a display or monitor on computing system 620. The computingsystem 620 comprises the software application of the present inventionthat uses the initial radiographic image as its input to automaticallydetect and determine high-Z objects, as described with respect to FIG.1.

The methods of the present invention can be used with all imaging systemconfigurations regardless of the approach employed to create therelative motion between the radiation source and the object beinginspected. These imaging system configurations include, but are notlimited to, portal (i.e. drive-through); mobile (e.g. imaging systems ontrucks, straddle carriers, etc.); gantry (i.e. moves along rails ortracks); and, car wash (employ vehicle transport systems to movevehicles through an X-ray building or tunnel).

In one embodiment, system 600 is a high-energy penetrating X-ray system,such as one that employs a linear accelerator X-ray source withaccelerating potential in the millions of volts (MV). In one example,the high-Z detection methods of the present invention are implemented onRapiscan Systems' 6 MV Eagle™ Portal cargo inspection system and isdirectly extended to Rapiscan Systems' Eagle™ Classic and Eagle™ Gantrysystems which employ the same 6 MV imaging system. In addition, thehigh-Z detection methods of the present invention is also ported toRapiscan Systems' 4.5 MV line of inspection systems, which includes theEagle Mobile, as well as Rapiscan System's 4.5 MV Portal and Gantrysystems that use similar X-ray imaging systems. Furthermore, the high-Zdetection methods of the present invention are also implemented withRapiscan Systems' 9 MV Portal, Gantry, or Mobile systems.

The high-Z detection methods of the present invention can also beimplemented in dual-energy cargo inspection systems that include X-raysources above approximately 3 MV. The present invention is directedtowards methods for detecting specific classes of materials (i.e.high-Z) within radiographic images, notwithstanding the method used toobtain the images or the energy of the X-ray or gamma-ray source that isemployed. Similarly, the high-Z detection methods of the presentinvention can be employed with other technologies and embodiments ofinspecting cargo.

In an alternate embodiment, an object under inspection is scanned twice,albeit at different angles, if a first scan indicates the presence of ahigh-Z item in an object under inspection. The methods of the presentinvention can, in some cases, generate an alarm due to randomsuperposition of materials along the radiation path length. In oneembodiment, data are collected for two or more views, such that thealarm can be resolved and false positives are further eliminated.

Referring back to FIG. 6, in one embodiment, in a first step, the X-raybeam 607 scans the container 615 at a first angle relative to thedirection of motion of the object under inspection, which is thecontainer 615. In one embodiment, the first scanning angle is 90degrees. The X-ray source 605 and detectors 610 are then aligned at asecond angle (which is, in one embodiment, different from the firstscanning angle) relative to the direction of motion of the container 615and a second scan is subsequently obtained. Thereafter, a “Clear” or“High-Z” decision is rendered by the method of the present invention byanalyzing both first and second radiographic scan images, taken atdifferent angles. Thus, if both images confirm the presence of a high-Zobject, an alarm is rendered.

In one configuration, the X-ray scanning system 600 is mounted on amobile inspection vehicle so that the second scan is generated by movingthe inspection vehicle relative to the container 615. In anotherconfiguration, the X-ray scanning system 600 is mounted on a gantry andthe second scan is generated by moving the gantry relative to thecontainer 615.

In another embodiment, the X-ray scanning system 600 comprises twodetector arrays positioned at an angle relative to one another. Forexample, the two detector arrays, in one embodiment, form a 10-degreeangle relative to one another. In this embodiment, the X-ray source 605irradiates the container 615 causing the two detectors to captureattenuated X-ray signals at different positions. Thereafter, a “Clear”or “High-Z” decision is rendered by the present invention by analyzingsignals from both detector arrays.

In one embodiment, the X-ray scanning system 600, modified with the useof two detector arrays angled relative to one another, is mounted on amobile inspection vehicle.

In a second embodiment, scanning system 600, comprising two detectorarrays at an angle relative to one another, is mounted on a gantry.

In a third embodiment, scanning system 600, comprising two detectorarrays at an angle relative to one another, has a collimator at itssource 605 that restricts the X-ray beam 607 while irradiating the twodetector arrays. The collimator, in one embodiment, is designed toenable one X-ray source to produce two narrow X-ray beams, separated byan angle; the collimator blocks the remainder of X rays from theemitting source. The advantage of this configuration is that two viewscan be obtained simultaneously, obviating the need (and the time) for asecond scan.

In a yet another embodiment, X-ray scanning system 600 completes a firstscan with the X-ray beam 607 at a first angle relative to the directionof motion of the container 615. In one embodiment, the first scan angleis 90 degrees. If the automated threat detection method of the presentinvention detects at least one threat object in the first scan image, asecond scan is conducted with the X-ray source 605 raised or lowered toobtain an image at a second scan angle, where the second scan angle isdifferent from the first scan angle, and is relative to the direction ofmotion of the container 615 and the detectors 610. Thereafter, a “Clear”or “High-Z” decision is rendered by the method of the present inventionby analyzing both radiographic scan images from the first scan andsecond scan, taken at different angles. For example, if both imagesconfirm the presence of a high-Z object, an alarm is rendered.

Persons of ordinary skill in the art would appreciate that theaforementioned dual-angle scan systems enable further reduction of falsealarm rates when used with the high-Z detection method of the presentinvention without substantially compromising on system throughput andcost.

The high-Z detection methods of the present invention can be used toenhance the performance of both dual- and multi-energy cargo inspectionsystems as well. First, the method described above with respect to FIG.1 can be applied to a high-energy radiographic image to provide ananalysis of the image that is orthogonal to the dual-energydetermination of the effective-Z of the material. This will helpalleviate some of the limitations of dual-energy imaging. Specifically,one limitation for large cargo containers is that due to the effect ofoverlapping materials having different densities and atomic numbers, theresult may be an inaccurate estimate of the effective Z. Additionally,the low-energy beam typically has a lower intensity and penetration thanthe high-energy beam. Thus, the low-energy image can become saturateddue to the low-energy beam being heavily attenuated by the cargo. As aresult, the signal-to-noise ratio is low and the dual-energy processcannot be successfully employed. In such cases, the high-Z detectionmethods of this invention will continue to operate on the high-energyimage, thus extending the range of penetration that the dual-energycargo inspection system can use to detect high-Z materials.

Secondly, the high-Z detection methods of the present invention can beapplied to the additional information provided by dual-energy imagingbelow the penetration limit of the low-energy image. FIG. 7 is a blockdiagram illustrating the steps of the dual-energy-based automatic high-Zdetection methods of the present invention. In one embodiment, thedual-energy-based high-Z detection methods of the present invention, instep 705, receives two radiographic images from a dual-energy X-rayimaging system 706, a low-energy image and a high-energy image.

Both the low-energy and the high-energy radiographic images 705 serve asinput to the dual-energy-based high-Z detection methods of the presentinvention. The images are subsequently processed within segmentationmodule 710. Within the attenuation segmentation block, in step 707, bothlow-energy and high-energy images are pre-processed using the sameapproach described in step 110 of FIG. 1, through the following twoseparate attenuation criteria, to determine regions that potentiallycontain high-Z objects:

ΣμL>=A_(low) and   EQUATION 2:

ΣμL>=A_(high)   EQUATION 3:

where L is thickness and μ is the linear attenuation coefficient of theobject under inspection and A_(low) and A_(high) are predeterminedattenuation values in the low-energy and high-energy images,respectively. Persons of ordinary skill in the art should note thatsince there is a difference in penetration power between the low-energyand high-energy X rays, the two aforementioned criteria, that processthe information separately, provide potentially useful information interms of the insufficient penetration region, among other characteristicinformation. A similar rule can be developed based on the transmissionof X rays.

In step 708, the dual-energy segmentation block processes the ratio ofthe pre-processed images with the following criterion, to calculateeffective-Z of the potential high-Z regions:

Σμ(E _(high))/Σμ(E _(low))>=T _(low−high)   EQUATION 4:

Where μ(E_(high)) and μ(E_(low)) are the absorption coefficientsestimated at the high- and low-energy images and the T_(low−high) is apredetermined value related to the effective Z of the object andsurrounding materials. It should be appreciated by those of ordinaryskill in the art that although the aforementioned ratio, T_(low−high),contains the contributions from all the materials along the X-ray path,the ratio is independent from that obtained by using attenuationcriteria in Equation 2 and 3. The dual-energy segmentation step 708indicates a different physical quantity, which has no object depth (L)dependence.

In one embodiment, the dual-energy information ratio is empiricallydetermined from a series of radiographic calibration images, which arecomprised of various combinations of high-, medium- and low-Z objectsand thicknesses of high-, medium- and low-Z overlapping materials. Thisprocess helps compensate for situations found in low attenuation andcontrast images, where the high-Z objects and neighboring cargo havingsimilar attenuation values.

In step 709 of processing spatial frequencies, anomalies that havecharacteristics different from the surrounding cargo are detected usinga low-pass filter such as the Gabor wavelet. For example, using Gaborwavelet the filtering criterion is the absolute value of Gabor filteredregion:

|G(x,y,θ)*I(x,y)|>=T _(G)   EQUATION 5:

where G(x,y, θ) and I(x,y) are the Gabor filter and the high-energyattenuation or transmission image, respectively, and T_(G) is athreshold that is pre-determined or dynamically set during the filteringprocess. The advantageous properties of the Gabor wavelet are itssensitivity to local spatial frequency and the invariance in angular andscaling space due to the band of functions covering scaling and angularspace for a given frequency range. Other characteristic filters can alsobe employed.

The image segmentation is performed by using a processor that loads froma memory device (hard disk, RAM, ROM, RAID array, flash drive, USBdevice, or other memory) the data representative of the two radiographicimages and that subjects the data to a program which performs the imagesegmentation calculations as described herein.

The image segmentation module 710 at this stage generates anintermediate image mask 715 of the segmented low-energy and high-energyradiographic images that is further subjected to a set of geometricalfilters and a gradient edge filter, at steps 716 and 717 respectively,aiming at the relatively low-attenuation threat objects embedded in ahighly cluttered cargo. Steps 716 and 717 are similar to those alreadydescribed with reference to step 110 and block 111 of FIG. 1 of thepresent invention and will not be discussed herein

Subsequently, the resultant final image mask 720, comprising at leastone suspicious area, is passed onto the characterization module 725. Thecharacterization module 725 analyzes each region within the image map720 and generates a feature matrix, which includes outputs of aplurality of functions within the characterization module 725—as havebeen earlier described with reference to the single-energy methods ofFIG. 1. However, the dual-energy-based threat detection methods of thepresent invention differ in the sense that to further improve Zestimation, the contribution to the effective-Z due to overlappingmaterials is determined and used to estimate, in step 723, the neteffective-Z of the potential high-Z object. Additionally, in step 724,if it is determined that there is too low a signal-to-noise ratio (SNR)with reference to the low-energy image data, only the high-energy imagedata are used to render a decision on high-Z threats using the stepsshown in FIG. 1.

Subsequently, the resulting feature vectors for each potential high-Zarea, combining the results of performing the steps in FIG. 1 and FIG.7, are evaluated against established decision-making rules, by thedecision block 730, to determine whether a high-Z object is present andto render a “clear” or “high-Z” decision 735. It should be noted hereinthat while the decision-making methods of this embodiment are similar tothat of the single-energy case, specific rules are implemented to dealwith feature vectors from dual-energy data.

While the present invention describes methods employing dual-energyradiography, the methods are extensible to other radiographic methods,such as those employing multiple energies and dual-species radiographywhere both neutrons and X rays or gamma rays are employed. It should beappreciated that the present invention has been described in accordancewith multiple different embodiments. Other features, functions, orstructures which are equivalent to the ones disclosed herein or obviousalternatives to a person of ordinary skill in the art are intended to bepart of, and encompassed by, the present invention.

1. An inspection system comprising: a. a radiation source; b. a detectorarray; c. an inspection region bounded by said radiation source anddetector array; d. a processing unit, wherein, through operation of atleast one processor, at least one memory, and programmatic instructions,said processing unit i. obtains data representative of a radiographicimage; ii. segments said data based on radiation attenuation ortransmission; iii. identifies at least one segmented area within saiddata representative of said radiographic image; iv. filters said atleast one segmented area using at least one geometric filter; v.generates a plurality of feature vectors using said filtered segmentedarea; and vi. compares said feature vectors against predefined values todetermine whether a high-atomic-number object is present.
 2. Theinspection system of claim 1 wherein said radiographic image has aspatial resolution of at least 0.25% of a minimum size of a threatobject.
 3. The inspection system of claim 1 wherein said radiationsource is at least one of X-ray or gamma-ray radiation.
 4. Theinspection system of claim 1 wherein said processing unit generates amap of said segmented data representative of said radiographic image bydetermining local maximum peak attenuation values.
 5. The inspectionsystem of claim 1 wherein said processing unit generates a map of saidsegmented data representative of said radiographic image by determiningminimum transmission values and applying edge gradient calculations. 6.The inspection system of claim 1 wherein said geometric filter is atleast one of shape, symmetry, size or homogeneity.
 7. The inspectionsystem of claim 6 wherein said size filter is applied to at least onesegmented area to identify dimensions selected on the basis of spatialresolution or penetration.
 8. The inspection system of claim 6 whereinsaid shape filter is applied to at least one segmented area to identifya spatial aspect ratio of less than
 20. 9. The inspection system ofclaim 6 wherein said segmented area has a first number of pixels andwherein a second defined area has a second number of pixels and whereinthe homogeneity filter is applied to determine a ratio of said firstnumber of pixels to said second number of pixels.
 10. The inspectionsystem of claim 1 wherein said processing unit generates a plurality offeature vectors using said filtered segmented area by: a. Obtaining animage of said filtered segmented area; b. Estimating backgroundattenuation around said filtered segmented area; c. Subtracting thebackground attenuation from said filtered segmented area to generate anet attenuation of the filtered segmented area; d. Estimating dimensionsof the area of interest using said net attenuation of the filteredsegmented area; e. Calculating an attenuation of the filtered segmentedarea as if it were a high-Z material; and f. Comparing the calculatedattenuation of the filtered segmented area of interest to the netattenuation of the filtered segmented area.
 11. The inspection system ofclaim 1 wherein said feature vectors comprise at least one of maximumattenuation, net attenuation, a ratio of attenuation to an area of asuspicious object, a gradient of a suspicious object along a boundary,and a difference produced between measured background correctedattenuation and calculated attenuation.
 12. The inspection system ofclaim 1 wherein said feature vectors are compared against predefinedvalues to determine whether a high-atomic-number object is present. 13.An inspection system comprising a processing unit, wherein saidprocessing unit: i. segments data of a first radiographic image, whichis representative of a first view of an object, and a secondradiographic image, which is representative of a second view of theobject, based on radiation attenuation or transmission; ii. filters atleast one segmented area using at least one filter for each of saidimages; iii. generates a plurality of feature vectors using saidfiltered segmented area for each of said images; and iv. determineswhether a high-atomic-number object is present using said featurevectors for each of said images.
 14. The inspection system of claim 13wherein each of said radiographic images is produced using at least oneof an X-ray or gamma-ray radiation source.
 15. The inspection system ofclaim 13 wherein said processing unit activates an alarm if each of saidimages indicates the presence of a high atomic number object.
 16. Theinspection system of claim 13 wherein said filter is at least one ofshape, symmetry, size or homogeneity.
 17. The inspection system of claim16 wherein said size filter filters said at least one segmented area toidentify dimensions selected on the basis of the inspection system'sspatial resolution or penetration.
 18. The inspection system of claim 16wherein said shape filter filters said at least one segmented area toidentify a spatial aspect ratio of less than
 20. 19. An inspectionsystem comprising a processing unit, wherein said processing unit: i.segments data of a first radiographic image, which is representative ofan object and generated at a first energy level, and a secondradiographic image, which is representative of the object and generatedat a second energy level; ii. filters at least one segmented area usingat least one filter for each of said images; iii. generates a pluralityof feature vectors using said filtered segmented area for each of saidimages; iv. performs a ratio operation on said plurality of featurevectors, resulting in a ratio feature vector; and v. determines whethera high-atomic-number object is present using said ratio feature vector.20. The inspection system of claim 19 wherein said processing unitactivates an alarm if each of said images indicates the presence of ahigh atomic number object.